Development and Testing

Development and Testing often require quick turnaround on using smaller amounts of resources or interactive activities. See the available option for interactive or small-scale testing work below.

Warning:

Do not run full-scale (normal) analyses on login nodes. The main approach to run computational analyses is through writing job scripts and sending them to the scheduler to run. See also Some interfaces like Open OnDemand, JupyterHub, and Galaxy can manage job scheduling behind the scenes and may be more convenient than job submission from the command-line when appropriate.

Only run workloads from blue storage. This is a fast storage systems that can handle the I/O involved in research workloads. Before using sbatch or launching a workload interactively, make sure your working directory is a blue file path, e.g. /blue/<group>/<user>, and not your /orange or /home directory (~ or /home/<user>). Use pwd to print working directory.

Login Nodes

Running resource intensive applications on the login nodes is against HPG usage policy. Learn more at HPG Computation. Interactive work other than managing jobs and data is discouraged on the login nodes. However, short test jobs (processes) are permitted as long as they fall within the following limits.

1. No more than 16 cores
2. No longer than 10 minutes (wall time)
3. No more than 64 GB of RAM.

That above resource limits essentially define what we mean by a “small, short” job or process. These limits should allow for the testing of job submission scripts or even simple application development tests. If you need to run multiple instances of some process (gzip, make, cp, etc), you should observe the above limits and not run more than 16 simultaneous instances of any single process nor should the collection of such processes consume more than 64 GB of RAM.

Data management operations such as gzip, rsync, scp sftp, etc. can take a long time to complete and are exempt from the 10 minute time limit. If you have development and testing requirements that exceed the above resource limits there are several options as described below.

SLURM Interactive Session

You can request resources for an interactive session (i.e. job) and start a command shell (bash, for example). Within that command shell you will have access to the resources you requested and can run whatever commands and processes you wish. Consider the example below. It will give you 4 GB of memory for 8 hours on a real compute host and present you, once the job starts, with an interactive command shell (bash). From that shell you can run commands and launch processes just as you would from any other host (login or otherwise).

$ srun --mem=4gb --time=08:00:00 --pty bash -i

Note: Because the requested resources must be allocated and scheduled by the batch scheduler, it could take any where from a few seconds to a few hours for your interactive session to start. How long it takes depends on many factors that include how busy the system is overall and what percentage of your group's allocation is already in use.

See the SchedMD srun documentation for further information and details regarding the srun command.

SLURM Development Session

A small number of servers have been placed into a SLURM partition (collection of hosts) for the purpose of supporting just software development. Jobs in this partition are not subject to a user's normal QOS limits. You can access the partition by specifying the "dev" partition to the appropriate SLURM command. For example, to obtain a resources for an interactive session (job) in the dev partition you could run the following command.

srun --partition=hpg-dev --mem=4gb --time=04:00:00 --pty bash -i
#or if you need more cores: srun --partition=hpg-dev --mem=4gb --ntasks=1 --cpus-per-task=8 --time=04:00:00 --pty bash -i 

By loading the ufrc environment module, you can take advantage srundev and simpify the above to,

module load ufrc
srundev --mem=4gb --ntasks=1 --cpus-per-task=8 --time=04:00:00 

The srundev command is a wrapper encapsulating srun --partition=hpg-dev --pty bash -i.

Note: The default time limit for the SLURM development partition is 00:10:00 (10 minutes). The maximum time limit in the development partition is 12 hours.

Pre-Allocation of Resources

Finally, you can also use salloc to create a SLURM allocation under which you can run commands or scripts with srun for as long as the allocation is valid. Whatever you srun under the allocation will be executed within the context of the allocated resources but there will be no delay since the resources have already been allocated.

Expand to see an example

$ salloc -n 1 --cpus-per-task=2 --mem=8gb --time=10:00:00
salloc: Pending job allocation 52219029
salloc: job 52219029 queued and waiting for resources
salloc: job 52219029 has been allocated resources
salloc: Granted job allocation 52219029

[chasman@login4 slurm]$ printenv | grep SLURM
SLURM_NODELIST=c6a-s26
SLURM_JOB_NAME=bash
SLURM_NODE_ALIASES=(null)
SLURM_JOB_QOS=ufhpc
SLURM_NNODES=1
SLURM_JOBID=52219029
SLURM_NTASKS=1
SLURM_TASKS_PER_NODE=1
SLURM_CPUS_PER_TASK=2
SLURM_JOB_ID=52219029
SLURM_SUBMIT_DIR=/home/chasman
SLURM_NPROCS=1
SLURM_JOB_NODELIST=c6a-s26
SLURM_CLUSTER_NAME=hipergator
SLURM_JOB_CPUS_PER_NODE=2
SLURM_SUBMIT_HOST=login4.ufhpc
SLURM_JOB_PARTITION=hpg-default
SLURM_JOB_ACCOUNT=ufhpc
SLURM_JOB_NUM_NODES=1
SLURM_MEM_PER_NODE=8192

Interactive Terminals

You can get a more familiar Interactive Terminal similar to what you could open on a local workstation via a web or GUI environment. We offer Open OnDemand where you can select between a terminal session and a full Linux desktop (Xfce4) or a terminal in a JupyterLab session in JupyterHub.

Avoiding Session Interruption

It is possible to have multiple sessions running simultaneously. HiPerGator offers options for terminal multiplexing. See Persistent Terminal Sessions for more details.